a  d@sddlZddlmZddlmZddlmZmZGdddejZGdd d ejZ Gd d d ejZ e Gd d d ejZ dS)N)nn) ARCH_REGISTRY)Upsample make_layercs*eZdZdZdfdd ZddZZS)ChannelAttentionzChannel attention used in RCAN. Args: num_feat (int): Channel number of intermediate features. squeeze_factor (int): Channel squeeze factor. Default: 16. c s\tt|ttdtj|||dddtjddtj|||dddt|_ dS)Nrr)paddingT)Zinplace) superr__init__r SequentialZAdaptiveAvgPool2dConv2dReLUZSigmoid attention)selfnum_featsqueeze_factor __class__`/var/www/html/stable-diffusion-webui/venv/lib/python3.9/site-packages/basicsr/archs/rcan_arch.pyr s $zChannelAttention.__init__cCs||}||SN)r)rxyrrrforwards zChannelAttention.forward)r__name__ __module__ __qualname____doc__r r __classcell__rrrrrsrcs*eZdZdZdfdd ZddZZS) RCABaResidual Channel Attention Block (RCAB) used in RCAN. Args: num_feat (int): Channel number of intermediate features. squeeze_factor (int): Channel squeeze factor. Default: 16. res_scale (float): Scale the residual. Default: 1. rrc sRtt|||_tt||dddtdt||dddt|||_ dS)NrT) r r!r res_scalerr r rrrcab)rrrr#rrrr $s (z RCAB.__init__cCs|||j}||Sr)r$r#rrresrrrr,sz RCAB.forward)rrrrrrrr!sr!cs*eZdZdZdfdd ZddZZS) ResidualGroupa!Residual Group of RCAB. Args: num_feat (int): Channel number of intermediate features. num_block (int): Block number in the body network. squeeze_factor (int): Channel squeeze factor. Default: 16. res_scale (float): Scale the residual. Default: 1. rrcs:tt|tt||||d|_t||ddd|_dS)N)rrr#r"r) r r'r rr!residual_grouprr conv)rr num_blockrr#rrrr ;s  zResidualGroup.__init__cCs|||}||Sr)r)r(r%rrrrBszResidualGroup.forward)rrrrrrrr'1s r'cs*eZdZdZd fd d Zd d ZZS)RCANaResidual Channel Attention Networks. Paper: Image Super-Resolution Using Very Deep Residual Channel Attention Networks Ref git repo: https://github.com/yulunzhang/RCAN. Args: num_in_ch (int): Channel number of inputs. num_out_ch (int): Channel number of outputs. num_feat (int): Channel number of intermediate features. Default: 64. num_group (int): Number of ResidualGroup. Default: 10. num_block (int): Number of RCAB in ResidualGroup. Default: 16. squeeze_factor (int): Channel squeeze factor. Default: 16. upscale (int): Upsampling factor. Support 2^n and 3. Default: 4. res_scale (float): Used to scale the residual in residual block. Default: 1. img_range (float): Image range. Default: 255. rgb_mean (tuple[float]): Image mean in RGB orders. Default: (0.4488, 0.4371, 0.4040), calculated from DIV2K dataset. @ rro@gw#?g8EGr?gB`"?c stt|| |_t| dddd|_t ||ddd|_ t t |||||d|_ t ||ddd|_t|||_t ||ddd|_dS)Nrr")rr*rr#)r r+r img_rangetorchZTensorviewmeanrr conv_firstrr'bodyconv_after_bodyrupsample conv_last) rZ num_in_chZ num_out_chrZ num_groupr*rZupscaler#r1Zrgb_meanrrrr `s  z RCAN.__init__cCsd|j||_||j|j}||}|||}||7}|||}||j|j}|Sr)r4Ztype_asr1r5r7r6r9r8r%rrrr|s z RCAN.forward)r,r-rrr.rr/r0rrrrrr+Gsr+) r2rZbasicsr.utils.registryrZ arch_utilrrModulerr!r'registerr+rrrrs